Power transmission scene hidden danger target distance measurement precision compensation method, system, medium and equipment
By constructing a ranging accuracy compensation model and a graph optimization algorithm, and combining 3D point cloud and 2D image data, the distance measurement from the potential hazard target to the power transmission line is optimized, solving the problem of insufficient ranging accuracy in the existing technology and achieving higher accuracy and better system adaptability.
Patent Information
- Application Number
- CN202410589862.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-05-13
- Publication Date
- 2025-11-21
AI Technical Summary
Existing methods for ranging potential hazards in power transmission scenarios lack accuracy, especially in the process of measuring distances between 3D threat models and power transmission lines, where calculation errors are significant, affecting the accuracy of the ranging results.
By constructing a ranging accuracy compensation model, using graph optimization algorithms to optimize the parameters of the preset ranging accuracy compensation model, combining the calibration mapping relationship between three-dimensional point cloud data and two-dimensional images of the power transmission scenario, filtering ground point cloud data and generating elevation point data, calculating the predicted distance and the actual distance from the hidden danger target to the power transmission line, and optimizing the ranging accuracy compensation model to improve ranging accuracy.
Without relying on real-time point cloud data, accurate ranging of potential hazards is achieved by fusing real-time two-dimensional image data, which improves ranging accuracy and enhances the robustness of the system.
Smart Images
Figure CN120997273A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application belongs to the technical field of power transmission scene hidden target ranging, and particularly relates to a power transmission scene hidden target ranging precision compensation method and system, a medium and equipment. BACKGROUND
[0002] The statements in this section merely provide background information related to the present application and do not necessarily constitute prior art.
[0003] In power transmission line operation and maintenance, the construction machinery, trees, buildings and other targets existing in the scene of the power transmission line channel direction need to be monitored, and the distance between the target and the power transmission conductor is calculated to accurately measure the harm degree of the hidden target to the power transmission line. When there is a threat to the power transmission line, timely alarm and notification of relevant personnel for processing are performed to ensure the safety of the power transmission line channel.
[0004] The existing power transmission scene hidden target ranging usually adopts a plane laser point cloud ranging method, which uses a statistical average method to improve the distance between the discrete points and the laser radar device, and the application scene and the means to improve the precision are very limited. In addition, the prior art also provides a power transmission line multi-dimensional environment monitoring scheme for a three-dimensional ranging device, which constructs a three-dimensional threat model according to the ranging information set and the position corresponding relationship of the dangerous source, and identifies the dangerous source by compensating the three-dimensional threat model from the perspective of the dangerous source. However, in the three-dimensional threat model and power transmission line ranging process, there is still a calculation error, which affects the accuracy of the ranging result. SUMMARY
[0005] In order to solve the above technical problems, the present application provides a power transmission scene hidden target ranging precision compensation method, system, medium and equipment, which constructs a ranging precision compensation model to improve the ranging precision of the power transmission scene hidden target.
[0006] In order to achieve the above purpose, the present application adopts the following technical solutions:
[0007] The first aspect of the present application provides a power transmission scene hidden target ranging precision compensation method.
[0008] In one or more embodiments, a power transmission scene hidden target ranging precision compensation method is provided, comprising:
[0009] Obtaining power transmission scene three-dimensional point cloud data, power transmission scene two-dimensional image and a calibration mapping relationship, segmenting first ground point cloud data and power line point cloud data from the power transmission scene three-dimensional point cloud data, and then screening second ground point cloud data projected in the range of the power transmission scene two-dimensional image from the segmented first ground point cloud data;
[0010] According to the screened second ground point cloud data, height point data is generated and projected into the power transmission scene two-dimensional image, and in combination with the width of the hidden danger target, corresponding rectangular frame data is generated in the power transmission scene two-dimensional image and associated with the height point data;
[0011] The rectangular frame data is processed to obtain a predicted distance value of the hidden danger target to the power transmission line; according to the rectangular frame data associated with the height point data, the minimum distance of each height point to the power transmission line point cloud is calculated and taken as the true distance value of the hidden danger target to the power transmission line of the corresponding height point;
[0012] According to the predicted distance value and the true distance value of the hidden danger target to the power transmission line, the parameters of the preset ranging accuracy compensation model are optimized to obtain an optimized ranging accuracy compensation model, so as to construct a mapping relationship between the predicted distance value of the hidden danger target to the power transmission line of the height point and the accuracy compensation value thereof;
[0013] Based on the optimized ranging accuracy compensation model, the accuracy compensation value corresponding to the predicted distance value of the hidden danger target to the power transmission line of the corresponding height point is obtained, and the two are superimposed to obtain the final distance value of the hidden danger target to the power transmission line of the corresponding height point.
[0014] As an implementation mode, the parameters of the preset ranging accuracy compensation model are optimized based on a graph optimization algorithm.
[0015] The above technical solution has the advantages that the graph optimization algorithm, a nonlinear optimization method, is used to improve the parameter optimization accuracy of the preset ranging accuracy compensation model, thereby improving the final distance value of the hidden danger target to the power transmission line of the corresponding height point.
[0016] As an implementation mode, the process of optimizing the parameters of the preset ranging accuracy compensation model based on the graph optimization algorithm is as follows:
[0017] In the world coordinates where the hidden danger target is located, each parameter in the preset ranging accuracy compensation model is constructed as a node of a graph, the difference between each predicted distance value and the corresponding true distance value is constructed as an error term and a edge of the graph, the optimization variable and the error term are connected by a unary edge, and a graph optimization problem is established;
[0018] The Jacobian matrix of each error term with respect to the optimization variable is calculated;
[0019] The gradient is calculated by solving the Jacobian matrix to determine the update direction and step length of the optimization variable, and the value of the optimization variable is updated in the iteration process, so as to minimize the error term and obtain the parameters of the optimized ranging accuracy compensation model.
[0020] The advantage of the above technical solution is that the error value between the predicted distance value and the corresponding real distance value can be minimized by using the graph optimization algorithm, thereby improving the final distance value of the hidden danger target to the power transmission line of the corresponding height point.
[0021] As an implementation form, the width of the rectangular frame data is greater than or equal to the width of the hidden danger target.
[0022] The advantage of the above technical solution is that the rectangular frame data can be closer to the actual hidden danger target, thereby more accurately determining the distance value of the actual hidden danger target to the power transmission line.
[0023] As an implementation form, the rectangular frame data is processed by using a preset ranging algorithm to obtain a predicted distance value of the hidden danger target to the power transmission line.
[0024] The advantage of the above technical solution is that the predicted distance value of the hidden danger target to the power transmission line is obtained based on the rectangular frame data without changing the preset ranging algorithm, thereby providing a data basis for optimizing the predicted distance value.
[0025] As an implementation form, after the second ground point cloud data is screened out, and before the height point data is generated, the method further includes:
[0026] The screened second ground point cloud data is subjected to data enhancement.
[0027] The advantage of the above technical solution is that the density of the second ground point cloud data can be improved, thereby improving the accuracy of the generated height point data.
[0028] The second aspect of the present application provides a power transmission scene hidden danger target ranging accuracy compensation system.
[0029] In one or more embodiments, a power transmission scene hidden danger target ranging accuracy compensation system includes:
[0030] A ground point cloud data screening module is configured to obtain three-dimensional point cloud data of a power transmission scene, a two-dimensional image of the power transmission scene, and a calibration mapping relationship therebetween, segment first ground point cloud data and power line point cloud data from the three-dimensional point cloud data of the power transmission scene, and screen second ground point cloud data projected within the range of the two-dimensional image of the power transmission scene from the segmented first ground point cloud data.
[0031] A rectangular frame data generation module is configured to generate height point data from the screened second ground point cloud data and project the height point data into the two-dimensional image of the power transmission scene, and in combination with the width of the hidden danger target, generate corresponding rectangular frame data in the two-dimensional image of the power transmission scene and associate the rectangular frame data with the height point data.
[0032] a prediction and real distance value calculation module, configured to process the rectangular frame data to obtain a predicted distance value of the hidden danger target to the power transmission line, and calculate a minimum distance from each height point to the power transmission line point cloud as a real distance value of the hidden danger target to the power transmission line of the corresponding height point according to the rectangular frame data associated with the height point data;
[0033] a precision compensation model optimization module, configured to optimize parameters of a preset ranging precision compensation model according to the predicted distance value and the real distance value of the hidden danger target to the power transmission line, to obtain an optimized ranging precision compensation model, and to construct a mapping relationship between the predicted distance value of the hidden danger target to the power transmission line of the height point and the precision compensation value thereof;
[0034] a predicted distance value compensation module, configured to obtain a precision compensation value corresponding to the predicted distance value of the hidden danger target to the power transmission line of the corresponding height point based on the optimized ranging precision compensation model, and to obtain a final distance value of the hidden danger target to the power transmission line of the corresponding height point by superimposing the predicted distance value and the precision compensation value.
[0035] As an implementation form, in the precision compensation model optimization module, the parameters of the preset ranging precision compensation model are optimized based on a graph optimization algorithm, and the process is as follows:
[0036] In the world coordinates where the hidden danger target is located, each parameter in the preset ranging precision compensation model is constructed as a node of a graph with the optimization variable, and the difference between each predicted distance value and the corresponding real distance value is constructed as an error term and a edge of the graph, the optimization variable and the error term are connected by a unary edge, and a graph optimization problem is established;
[0037] The Jacobian matrix of each error term relative to the optimization variable is calculated.
[0038] The gradient is calculated by solving the Jacobian matrix to determine the update direction and step length of the optimization variable, and the value of the optimization variable is updated in the iteration process, so as to minimize the error term and obtain the parameters of the optimized ranging precision compensation model.
[0039] The above technical solution has the advantage that the graph optimization algorithm can minimize the error value between the predicted distance value and the corresponding real distance value, thereby improving the final distance value of the hidden danger target to the power transmission line of the corresponding height point.
[0040] A third aspect of the present application provides a computer readable storage medium.
[0041] A computer readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the steps of the power transmission scene hidden danger target ranging precision compensation method described above.
[0042] A fourth aspect of the present application provides an electronic device.
[0043] An electronic device comprises a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the steps in the power transmission scene hidden target ranging accuracy compensation method as described above when executing the program.
[0044] Compared with the prior art, the power transmission scene hidden target ranging accuracy compensation method has the following beneficial effects:
[0045] The power transmission scene hidden target ranging accuracy compensation method determines the predicted distance value and the real distance value of the hidden target to the power transmission line by using the known three-dimensional point cloud data of the power transmission scene and the calibration mapping of the two-dimensional image of the power transmission scene, optimizes the preset ranging accuracy compensation model, constructs the mapping relationship between the predicted distance value of the hidden target to the power transmission line and the accuracy compensation value of the elevation point, and finally optimizes the distance value of the hidden target to the power transmission line by superimposing the corresponding accuracy compensation value on the basis of the predicted distance value of the hidden target to the power transmission line at the corresponding elevation point, so that the ranging accuracy of the hidden target in the power transmission scene is improved without relying on real-time point cloud data and specific hidden target point cloud in the three-dimensional point cloud of the power transmission scene. BRIEF DESCRIPTION OF DRAWINGS
[0046] The drawings accompanying the specification of the present application form a part thereof and serve to provide further understanding of the present application, the exemplary embodiments of which and its description are used to explain the present application and do not constitute improper limitations on the present application.
[0047] Figure 1 is a flowchart of the power transmission scene hidden target ranging accuracy compensation method of the embodiment of the present application;
[0048] Figure 2 is a flowchart of the parameter optimization of the preset ranging accuracy compensation model based on the graph optimization algorithm of the embodiment of the present application;
[0049] Figure 3 is a structural schematic diagram of the power transmission scene hidden target ranging accuracy compensation system of the embodiment of the present application;
[0050] Figure 4 is a schematic diagram of an electronic device of the embodiment of the present application. DETAILED DESCRIPTION
[0051] The present application will be further described below in conjunction with the drawings and embodiments.
[0052] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as generally understood by those skilled in the art to which the present application belongs.
[0053] It is to be noted that the terms used herein are only intended to describe specific embodiments and are not intended to limit exemplary embodiments according to the present application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, steps, operations, devices, components and / or combinations thereof, but do not preclude the presence or addition of one or more other features, steps, operations, devices, components and / or combinations thereof.
[0054] Figure 1 is a flowchart of a power transmission scene hidden danger target ranging accuracy compensation method in an embodiment of the present application. As shown in the power transmission scene hidden danger target ranging accuracy compensation method in the embodiment shown in Figure 1 may include:
[0055] S101, obtaining power transmission scene three-dimensional point cloud data, power transmission scene two-dimensional image and mapping relationship therebetween, segmenting first ground point cloud data and power line point cloud data from the power transmission scene three-dimensional point cloud data, and screening second ground point cloud data projected within the range of the power transmission scene two-dimensional image from the segmented first ground point cloud data.
[0056] In the specific implementation process, the power transmission scene three-dimensional point cloud data can be collected by using a laser radar; and the power transmission scene two-dimensional image can be collected by using a camera.
[0057] According to the calibration of the two coordinate systems of the laser radar and the camera, the mapping relationship between the power transmission scene three-dimensional point cloud data and the power transmission scene two-dimensional image can be obtained.
[0058] In one or more embodiments, the power transmission scene three-dimensional point cloud data can be segmented based on a deep learning-based three-dimensional point cloud classification and segmentation algorithm. The segmented point cloud categories include, but are not limited to, power line point cloud data, first ground point cloud data, vegetation point cloud data and building point cloud data, etc.
[0059] Specifically, the deep learning-based three-dimensional point cloud classification and segmentation algorithm first extracts robust features from the original point cloud through a backbone network, and then fuses the features at different levels in the backbone network through a point cloud feature fusion module to obtain three-dimensional spatial features with better discrimination. On this basis, the semantic features are converted into instance embedding space through a joint instance semantic segmentation module, and the converted features and instance features are further fused to realize instance segmentation. The instance features are aggregated into the semantic feature space to promote semantic segmentation, and finally the instance classification is generated through a clustering algorithm on the instance features.
[0060] The three-dimensional point cloud segmentation and classification algorithm based on deep learning automatically performs fine point cloud segmentation on scene point cloud data, reduces additional artificial errors that may be introduced in the process of artificial point cloud segmentation, and improves the accuracy and processing efficiency of point cloud segmentation.
[0061] It should be noted that the selection of the three-dimensional point cloud classification and segmentation algorithm based on deep learning does not affect the final accuracy compensation result of the application.
[0062] S102, according to the screened second ground point cloud data, generating elevation point data and projecting into the power transmission scene two-dimensional image, and combining with the hazard target width, generating corresponding rectangular frame data in the power transmission scene two-dimensional image and associating with the elevation point data.
[0063] In the specific implementation process, after the second ground point cloud data is screened out, and before the elevation point data is generated, it further includes:
[0064] The screened second ground point cloud data is subjected to data enhancement.
[0065] For example, the interpolation algorithm is used to enhance the data of the screened ground point cloud data, so as to improve the scene ground point cloud density and improve the accuracy of the generation of the elevation point data.
[0066] It should be noted that other existing algorithms can be used to enhance the data of the second ground point cloud data, which will not be described in detail here.
[0067] The height range and interval of the elevation point data of the embodiment can be adapted according to the actual application scene, for example, the height range is from 0 to 15 meters, and the interval is 0.5 meters.
[0068] In the specific implementation process, the width of the rectangular frame data is greater than or equal to the width of the hazard target. In this way, the rectangular frame data can be closer to the actual hazard target, so that the distance value from the actual hazard target to the power transmission line can be determined more accurately.
[0069] The rectangular frame data is used to provide a data basis for the calculation of the predicted distance value of the hazard target to the power transmission line, and the rectangular frame data is adapted to the algorithm for processing the data.
[0070] S103, processing the rectangular frame data to obtain a predicted distance value of the hazard target to the power transmission line; according to the rectangular frame data associated with the elevation point data, calculating the minimum distance from each elevation point to the power transmission line point cloud and taking it as the true distance value of the hazard target to the power transmission line of the corresponding elevation point.
[0071] Specifically, the rectangular frame data is processed by using a preset ranging algorithm to obtain a predicted distance value of the hazard target to the power transmission line.
[0072] The preset distance measurement algorithm can be a fusion distance measurement model based on deep learning target detection and point cloud, and can be specifically selected by a person skilled in the art according to actual conditions, and details are not described herein.
[0073] In S104, parameters of the preset distance measurement accuracy compensation model are optimized according to the predicted distance value and the real distance value of the hidden danger target to the power transmission line, and an optimized distance measurement accuracy compensation model is obtained to construct a mapping relationship between the predicted distance value of the hidden danger target to the power transmission line and the accuracy compensation value of the height point.
[0074] In the embodiment, the preset distance measurement accuracy compensation model is as follows:
[0075]
[0076] wherein L is the accuracy compensation value, p is the predicted value, x and y are respectively the horizontal coordinate and the vertical coordinate of the hidden danger target in the world coordinate system, and k, a1, b1, c1, a2, b2 and c2 are parameters of the distance measurement accuracy compensation model.
[0077] Taking the distance measurement accuracy compensation model as an example, the parameters of the preset distance measurement accuracy compensation model are optimized based on a graph optimization algorithm.
[0078] Figure 2 A flowchart of the process of optimizing the parameters of the preset distance measurement accuracy compensation model based on the graph optimization algorithm is given. Figure 2 According to the process of optimizing the parameters of the preset distance measurement accuracy compensation model based on the graph optimization algorithm in the embodiment, the process is as follows:
[0079] In S201, under the world coordinate of the hidden danger target, each parameter in the preset distance measurement accuracy compensation model is constructed as a node of a graph, the difference between each predicted distance value and the corresponding real distance value is constructed as an error term and a side of the graph, and a graph optimization problem is established by using a unary side to connect the optimization variable and the error term.
[0080] Specifically, k, a1, b1, c1, a2, b2 and c2 in the distance measurement accuracy compensation model are taken as optimization variables and are constructed as nodes of the graph.
[0081] In S202, the Jacobian matrix of each error term with respect to the optimization variable is calculated.
[0082] The Jacobian matrix J(x, y) of each error term with respect to the optimization variable is expressed as follows:
[0083]
[0084] S203, the gradient is calculated by solving the Jacobian matrix to determine the update direction and step length of the optimization variable, and the value of the optimization variable is updated in the iteration process to minimize the error term, so as to obtain the parameters of the optimized ranging accuracy compensation model.
[0085] The ranging accuracy compensation model is constructed, the model parameters are solved based on the graph optimization algorithm, the ranging accuracy of the existing hidden danger target ranging algorithm is further compensated, and the ranging accuracy of the entire scene is improved.
[0086] It should be noted that the ranging accuracy compensation model can be implemented by using existing models such as gradient descent compensation model, which will not be described in detail here.
[0087] In other embodiments, other existing algorithms can also be used to optimize the process of preset ranging accuracy compensation model parameters, without affecting the final accuracy compensation result.
[0088] S105, based on the optimized ranging accuracy compensation model, the corresponding precision compensation value of the predicted distance value of the hidden danger target to the power transmission line of the corresponding elevation point is obtained, and the two are superimposed to obtain the final distance value of the hidden danger target to the power transmission line of the corresponding elevation point.
[0089] In this step, the mapping relationship between the predicted distance value of the hidden danger target of the elevation point (wherein the hidden danger target is represented by rectangular frame data) to the power transmission line and its accuracy compensation value can be realized by using the accuracy compensation quick lookup data graph, for example:
[0090] A data mapping graph of each second ground point cloud point in the two-dimensional image of the power transmission scene and the two-dimensional pixel point data of the image is established;
[0091] A data mapping graph of different rectangular frame heights at each ground pixel point in the two-dimensional image of the power transmission scene and the accuracy compensation value is established;
[0092] Through the above two data mapping graphs, the accuracy compensation quick lookup data graph is finally constructed.
[0093] The present application can solve the ranging accuracy compensation model parameters by real-time point cloud data, and can also generate the ranging accuracy compensation model parameters by historical point cloud data offline and further construct the accuracy compensation quick lookup data graph, which has good system adaptability and can greatly improve the processing efficiency of the entire system.
[0094] The present application does not depend on real-time point cloud data, and in the case that there is no specific hidden danger target point cloud in the scene point cloud, the accurate ranging of the hidden danger target can still be realized by fusing real-time image data, which has good system robustness.
[0095] Figure 3is a power transmission scene hidden target ranging accuracy compensation system structure diagram in an embodiment of the present application, the present embodiment corresponds to the power transmission scene hidden target ranging accuracy compensation method of Figure 1 , as shown in Figure 3 , the power transmission scene hidden target ranging accuracy compensation system in the present embodiment can include:
[0096] The ground point cloud data screening module 301 is configured to obtain power transmission scene three-dimensional point cloud data, power transmission scene two-dimensional image and mapping relationship between the two, segment first ground point cloud data and power line point cloud data from the power transmission scene three-dimensional point cloud data, and screen second ground point cloud data projected in the range of the power transmission scene two-dimensional image from the segmented first ground point cloud data;
[0097] The rectangular frame data generation module 302 is configured to generate elevation point data according to the screened second ground point cloud data and project the elevation point data into the power transmission scene two-dimensional image, and in combination with the hidden target width, generate corresponding rectangular frame data in the power transmission scene two-dimensional image and associate the rectangular frame data with the elevation point data;
[0098] The predicted and real distance value calculation module 303 is configured to process the rectangular frame data to obtain a predicted distance value of the hidden target to the power line, and calculate the minimum distance from each elevation point to the power line point cloud as the real distance value of the hidden target to the power line of the corresponding elevation point according to the rectangular frame data associated with the elevation point data;
[0099] The accuracy compensation model optimization module 304 is configured to optimize the parameters of a preset ranging accuracy compensation model according to the predicted distance value and the real distance value of the hidden target to the power line, obtain an optimized ranging accuracy compensation model, and construct the mapping relationship between the predicted distance value of the hidden target to the power line of the elevation point and the accuracy compensation value thereof;
[0100] The predicted distance value compensation module 305 obtains the accuracy compensation value corresponding to the predicted distance value of the hidden target to the power line of the corresponding elevation point based on the optimized ranging accuracy compensation model, and superimposes the predicted distance value and the accuracy compensation value to obtain the final distance value of the hidden target to the power line of the corresponding elevation point.
[0101] In the accuracy compensation model optimization module 304, the parameters of the preset ranging accuracy compensation model are optimized based on a graph optimization algorithm, and the process is as follows:
[0102] In the world coordinates where the hidden target is located, each parameter in the preset ranging accuracy compensation model is constructed as a node of a graph, the difference between each predicted distance value and its corresponding real distance value is constructed as an error term and a edge of the graph, and a unary edge is used to connect the optimization variable and the error term to establish a graph optimization problem;
[0103] calculating the Jacobian matrix of each error term with respect to the optimization variables;
[0104] The gradient is calculated by solving the Jacobian matrix to determine the update direction and step size of the optimization variables, and the value of the optimization variables is updated in the iteration process to minimize the error term, so as to obtain the parameters of the optimized ranging accuracy compensation model.
[0105] It should be noted that, Figure 3 each module in the power transmission scene hidden target ranging accuracy compensation system in Figure 1 each step in the power transmission scene hidden target ranging accuracy compensation method in
[0106] The embodiment determines the predicted distance value and the true distance value of the hidden target to the power transmission line by using the known power transmission scene three-dimensional point cloud data and the calibration mapping of the power transmission scene two-dimensional image, optimizes the preset ranging accuracy compensation model, constructs the mapping relationship between the predicted distance value of the hidden target to the power transmission line and the accuracy compensation value of the elevation point, and finally superimposes the corresponding accuracy compensation value on the basis of the predicted distance value of the hidden target to the power transmission line at the corresponding elevation point to optimize the distance value of the hidden target to the power transmission line. The embodiment realizes accurate ranging of the hidden target without relying on real-time point cloud data, and in the case that there is no specific hidden target point cloud in the power transmission scene three-dimensional point cloud, the accurate ranging of the hidden target can still be realized by fusing the power transmission scene two-dimensional real-time image data, has good system robustness, and improves the ranging accuracy of the hidden target in the power transmission scene.
[0107] Referring to Figure 4 , a schematic diagram of an electronic device is given. It should be noted that, Figure 4 The electronic device 400 shown is only an example and should not impose any limitations on the functions and use range of the embodiments of the present application.
[0108] As shown in Figure 4 , the electronic device 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 402 or programs loaded from a storage portion 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for system operation are also stored. The central processing unit 401, the ROM 402, and the RAM 403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.
[0109] The following components are connected to the I / O interface 405: an input part 406 including a keyboard, a mouse, etc.; an output part 407 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage part 408 including a hard disk, etc.; and a communication part 409 including a network interface card such as a local area network (LAN) card, a modem, etc. The communication part 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as necessary. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is attached to the drive 410 as necessary, so that a computer program read out therefrom is installed in the storage part 408 as necessary.
[0110] The central processing unit 401 in the electronic device of the present embodiment, when executing the program, realizes the steps in the power transmission scenario hazard target ranging accuracy compensation method as shown in Figure 1
[0111] In particular, according to the embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, the embodiments of the present application include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program codes for executing the method as shown in Figure 1 In such embodiments, the computer program can be downloaded and installed from a network by the communication part 409, and / or installed from the removable medium 411. When the computer program is executed by the central processing unit 401, various functions defined in the apparatus of the present application are executed.
[0112] The computer program instructions corresponding to the method as shown in Figure 1 The computer program instructions corresponding to the method as shown in Figure 1 The computer program instructions corresponding to the method as shown in Figure 1 The computer program instructions corresponding to the method as shown in
[0113] It is understood by those skilled in the art that all or part of the processes in the above-mentioned embodiments can be implemented by a computer program instructing relevant hardware, and the program can be stored in a computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), etc.
[0114] The above description is only the preferred embodiment of the present application, and is not intended to limit the present application. The present application can have various changes and modifications for those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims
1. A power transmission scene hidden danger target ranging accuracy compensation method, characterized in that, The method comprises the following steps: obtaining three-dimensional point cloud data of a power transmission scene, a two-dimensional image of the power transmission scene and a calibration mapping relationship between the two-dimensional image and the three-dimensional point cloud data, segmenting first ground point cloud data and power line point cloud data from the three-dimensional point cloud data of the power transmission scene, and then screening second ground point cloud data projected within the range of the two-dimensional image of the power transmission scene from the segmented first ground point cloud data; generating elevation point data according to the screened second ground point cloud data and projecting the elevation point data into the two-dimensional image of the power transmission scene, and then generating corresponding rectangular frame data in the two-dimensional image of the power transmission scene in combination with the width of a hidden danger target and associating the rectangular frame data with the elevation point data; processing the rectangular frame data to obtain a predicted distance value of the hidden danger target to the power line; calculating the minimum distance from each elevation point to the power line point cloud as the actual distance value of the hidden danger target to the power line for the corresponding elevation point according to the rectangular frame data associated with the elevation point data; optimizing the parameters of a preset ranging accuracy compensation model according to the predicted distance value and the actual distance value of the hidden danger target to the power line, obtaining an optimized ranging accuracy compensation model, and establishing a mapping relationship between the predicted distance value of the hidden danger target to the power line for the elevation point and the accuracy compensation value thereof; based on the optimized ranging accuracy compensation model, obtaining the accuracy compensation value corresponding to the predicted distance value of the hidden danger target to the power line for the corresponding elevation point, and superimposing the two values to obtain the final distance value of the hidden danger target to the power line for the corresponding elevation point.
2. The power transmission scene hazard target ranging accuracy compensation method of claim 1, wherein, The parameters of the preset ranging accuracy compensation model are optimized based on a graph optimization algorithm. 3.The power transmission scene hidden danger target ranging precision compensation method according to claim 2, characterized in that, The process of optimizing the parameters of the preset ranging accuracy compensation model based on the graph optimization algorithm comprises the following steps: in the world coordinates where the hidden danger target is located, constructing each parameter in the preset ranging accuracy compensation model as an optimization variable as a node of a graph, constructing the difference between each predicted distance value and the actual distance value corresponding thereto as an error term and as an edge of the graph, connecting the optimization variable and the error term using a unary edge, and establishing a graph optimization problem; calculating the Jacobian matrix of each error term with respect to the optimization variable; calculating the gradient by solving the Jacobian matrix to determine the update direction and step size of the optimization variable, updating the value of the optimization variable in the iteration process, and minimizing the error term as the target to obtain the parameters of the optimized ranging accuracy compensation model. 4.The power transmission scene hidden danger target ranging precision compensation method according to claim 1, characterized in that, The width of the rectangular frame data is greater than or equal to the width of the hidden danger target.
5. The power transmission scenario hazard target ranging accuracy compensation method of claim 1, wherein, The predicted distance value of the hidden danger target to the power line is obtained by processing the rectangular frame data using a preset ranging algorithm.
6. The power transmission scenario hazard target ranging accuracy compensation method of claim 1, wherein, After the second ground point cloud data is screened out, and before the elevation point data is generated, the method further comprises the following steps: performing data enhancement on the screened second ground point cloud data.
7. A power transmission scene hazard target ranging accuracy compensation system, characterized in that, The method comprises the following steps: a ground point cloud data screening module is configured to obtain three-dimensional point cloud data of a power transmission scene, a two-dimensional image of the power transmission scene and a calibration mapping relationship between the two-dimensional image and the three-dimensional point cloud data, segment first ground point cloud data and power line point cloud data from the three-dimensional point cloud data of the power transmission scene, and then screen second ground point cloud data projected within the range of the two-dimensional image of the power transmission scene from the segmented first ground point cloud data; a rectangular frame data generation module configured to generate height point data from the filtered second ground point cloud data, project the height point data into a two-dimensional image of the power transmission scene, and generate corresponding rectangular frame data in the two-dimensional image of the power transmission scene in combination with a width of the hidden danger target, and associate the rectangular frame data with the height point data; a predicted and real distance value calculation module configured to process the rectangular frame data to obtain a predicted distance value of the hidden danger target to the power transmission line; a rectangular frame data generation module configured to generate height point data from the filtered second ground point cloud data, project the height point data into a two-dimensional image of the power transmission scene, and generate corresponding rectangular frame data in the two-dimensional image of the power transmission scene in combination with a width of the hidden danger target, and associate the rectangular frame data with the height point data; a precision compensation model optimization module configured to optimize parameters of a preset distance measurement precision compensation model based on the predicted distance value and the real distance value of the hidden danger target to the power transmission line, to obtain an optimized distance measurement precision compensation model, and to construct a mapping relationship between the predicted distance value of the hidden danger target to the power transmission line and a precision compensation value of the height point; a predicted distance value compensation module configured to obtain a precision compensation value corresponding to the predicted distance value of the hidden danger target to the power transmission line based on the optimized distance measurement precision compensation model, and to obtain a final distance value of the hidden danger target to the power transmission line by superimposing the predicted distance value and the precision compensation value.
8. The power transmission scenario hazard target ranging accuracy compensation system of claim 7, wherein, In the precision compensation model optimization module, the parameters of the preset distance measurement precision compensation model are optimized based on a graph optimization algorithm, and the process is as follows: In the world coordinates of the hidden danger target, each parameter in the preset distance measurement precision compensation model is constructed as a node of a graph, the difference between each predicted distance value and its corresponding real distance value is constructed as an error term and a side of the graph, a unary side is used to connect the optimization variable and the error term, and a graph optimization problem is established; a Jacobian matrix of each error term with respect to the optimization variable is calculated; a gradient is calculated by solving the Jacobian matrix to determine the update direction and step size of the optimization variable, and the value of the optimization variable is updated in an iterative process to minimize the error term, and the parameters of the optimized distance measurement precision compensation model are obtained.
9. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the steps in the power transmission scene hidden danger target distance measurement precision compensation method of any one of claims 1-6.
10. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the program to implement the steps in the power transmission scene hidden danger target distance measurement precision compensation method of any one of claims 1-6.